Varying coefficient subdistribution regression for left-truncated semi-competing risks data
نویسندگان
چکیده
منابع مشابه
Nonparametric estimation with left truncated semi-competing risks data
SUMMARY Cause-specific hazard and cumulative incidence function are of practical importance in competing risks studies. Inferential procedures for these quantities are well developed and can be applied to semi-competing risks data, where a terminating event censors a non-terminating event, after coercing the data into the competing risks format. Complications arise when there is left truncation...
متن کاملAnalysis of left truncated and right censored competing risks data
In this article, the analysis of left truncated and right censored competing risks data is carried out, under the assumption of the latent failure times model. It is assumed that there are two competing causes of failures, although most of the results can be extended for more than two causes of failures. The lifetimes corresponding to the competing causes of failures are assumed to follow Weibu...
متن کاملQuantile Regression Based on Semi-Competing Risks Data
This paper considers quantile regression analysis based on semi-competing risks data in which a non-terminal event may be dependently censored by a terminal event. The major interest is the covariate effects on the quantile of the non-terminal event time. Dependent censoring is handled by assuming that the joint distribution of the two event times follows a parametric copula model with unspecif...
متن کاملSemi-Competing Risks Data Analysis
Hospital readmission is a key marker of quality of healthcare; it has been used to investigate variation in quality among patients in a broad range of clinical contexts and has become an important policy measure. Notwithstanding its widespread use, however, readmission remains controversial as a measure of quality. Among the concerns raised, whether and how patient deaths are handled in the ana...
متن کاملRegression analysis for cumulative incidence probability under competing risks and left-truncated sampling.
The cumulative incidence function provides intuitive summary information about competing risks data. Via a mixture decomposition of this function, Chang and Wang (Statist. Sinca 19:391-408, 2009) study how covariates affect the cumulative incidence probability of a particular failure type at a chosen time point. Without specifying the corresponding failure time distribution, they proposed two e...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2014
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2014.06.005